The use of radiation to treat medical conditions comprises a known area of prior art endeavor. For example, radiation therapy comprises an important component of many treatment plans for reducing or eliminating unwanted tumors. Unfortunately, applied radiation does not inherently discriminate between unwanted materials and adjacent healthy tissues, organs, or the like that are desired or even critical to continued survival of the patient. As a result, radiation is ordinarily applied in a carefully administered manner to at least attempt to restrict the radiation to a given target volume.
Treatment plans typically serve to specify any number of operating parameters as pertain to the administration of such treatment with respect to a given patient. For example, many treatment plans provide for exposing the target volume to possibly varying dosages of radiation from a number of different directions using variable beam shapes. Arc therapy, for example, comprises one such approach.
Such treatment plans are often optimized prior to use. (As used herein, “optimization” will be understood to refer to improving upon a candidate treatment plan without necessarily ensuring that the optimized result is, in fact, the singular best solution.) Many optimization approaches use an automated incremental methodology where various optimization results are calculated and tested in turn using a variety of automatically-modified (i.e., “incremented”) treatment plan optimization parameters.
Many treatment plans provide for delivering radiation towards a target tissue from a plurality of different angles. Such an approach may create so-called hotspots (i.e., local volumes of higher radiation doses) in healthy tissue. By one approach hotspots are attempted to be minimized or reduced by imposing a constraint (representing a limit on the radiation dose to be received by the healthy tissue) on specifically-identified healthy tissues and determining a treatment plan while observing that constraint.
Pursuant to another known approach, instead of using a same constraint value for all portions of the healthy tissue, the constraint can vary spatially such that healthy tissue closer to the targeted volume is imposed with a higher constraint value while healthy tissue further away from the treatment volume is imposed with a lower constraint value. Generally speaking this approach seeks to observe a rapid fall-off in dosing levels as the distance from the target volume increases and accordingly the fall-off curve is presumed/represented as being exponential.
While suitable for at least some application settings, the foregoing approaches do not necessarily meet all needs in these regards.
Elements in the figures are illustrated for simplicity and clarity and have not necessarily been drawn to scale. For example, the dimensions and/or relative positioning of some of the elements in the figures may be exaggerated relative to other elements to help to improve understanding of various embodiments of the present invention. Also, common but well-understood elements that are useful or necessary in a commercially feasible embodiment are often not depicted in order to facilitate a less obstructed view of these various embodiments of the present invention. Certain actions and/or steps may be described or depicted in a particular order of occurrence while those skilled in the art will understand that such specificity with respect to sequence is not actually required. The terms and expressions used herein have the ordinary technical meaning as is accorded to such terms and expressions by persons skilled in the technical field as set forth above except where different specific meanings have otherwise been set forth herein.